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ICASSP
2011
IEEE
13 years 5 days ago
Empirical divergence maximization for quantizer design: An analysis of approximation error
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Michael A. Lexa
CORR
2008
Springer
119views Education» more  CORR 2008»
13 years 8 months ago
BER and Outage Probability Approximations for LMMSE Detectors on Correlated MIMO Channels
This paper is devoted to the study of the performance of the linear minimum mean-square error (LMMSE) receiver for (receive) correlated multiple-input multiple-output (MIMO) system...
Abla Kammoun, Malika Kharouf, Walid Hachem, Jamal ...
TASLP
2010
117views more  TASLP 2010»
13 years 3 months ago
Speech Enhancement Using Gaussian Scale Mixture Models
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski
INTERSPEECH
2010
13 years 3 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
ICML
2002
IEEE
14 years 9 months ago
Univariate Polynomial Inference by Monte Carlo Message Length Approximation
We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample. It partiti...
Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison